A growing body of literature has shown that being victimized online is associated with poor mental health. Little is known about the factors that protect youth from the negative outcomes that may result from these victimization experiences, particularly those related to race. Using a risk and resilience framework, this study examined the protective function of ethnic identity and self-esteem among African Americans who experience online racial discrimination. For the sample of 125 adolescents, hierarchical regression results revealed that higher levels of ethnic identity and self-esteem significantly moderated the negative impact of online racial discrimination on anxiety levels. These findings show that ethnic identity and self-esteem can buffer the negative mental health outcomes associated with online racial discrimination, at least with respect to adolescents' anxiety. Findings from the current study have significant implications for adolescent adjustment given the increased time youth spend doing online activities.

Abstract.Convective

Convective quasi-equilibrium (QE) has for several decades stood as a key postulate for parametrization of the impacts of moist convection at small scales upon the large-scale flow. Departures from QE have motivated stochastic convective parametrization, which in its early stages may be viewed as a sensitivity study. Introducing plausible stochastic terms to modify the existing convective parametrizations can have substantial impact, but, as for so many aspects of convective parametrization, the results are sensitive to details of the assumed processes. We present observational results aimed at helping to constrain convection schemes, with implications for each of conventional, stochastic or 'superparametrization' schemes. The original vision of QE due to Arakawa fares well as a leading approximation, but with a number of updates. Some, like the imperfect connection between the boundary layer and the free troposphere, and the importance of free-tropospheric moisture to buoyancy, are quantitatively important but lie within the framework of ensemble-average convection slaved to the large scale. Observations of critical phenomena associated with a continuous phase transition for precipitation as a function of water vapour and temperature suggest a more substantial revision. While the system's attraction to the critical point is predicted by QE, several fundamental properties of the transition, including high precipitation variance in the critical region, need to be added to the theory. Long-range correlations imply that this variance does not reduce quickly under spatial averaging; scaling associated with this spatial averaging has potential implications for superparametrization. Long tails of the distribution of water vapour create relatively frequent excursions above criticality with associated strong precipitation events.

[1] For the first time, a stochastic deep convective parameterization to represent variability arising from small-scale processes that are unresolved by traditional deterministic moist convective parameterizations is tested in a general circulation model. Two physical pathways of representing small-scale variability as a stochastic process are explored. First, the relationship between cloud-base mass flux M b and large-scale convective available potential energy (CAPE) is posited to have a stochastic component (the CAPE-M b scheme). Second, the vertical structure of heating is modified by a simple random process about the structure given by the traditional convective scheme (the VSH scheme). The CAPE-M b scheme increases the overall variance of precipitation toward observations with a realistic spatial pattern. The VSH scheme has smaller impacts on precipitation variance but yields preferential enhancement at large spatial scales and low frequencies.